$ loading_
Manage Databricks clusters, jobs, SQL, and catalogs through MCP tools.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "databricks-mcp" yet — see the docs or source repo.
List all clusters in the current Databricks workspace and show their names, states, runtime versions, and creators; also mark any terminated clusters.
A structured cluster inventory for quickly reviewing current compute resource status.
Fetch the 10 most recent Databricks job runs, sorted by start time descending, showing job name, run state, duration, and failure reason, then summarize abnormal runs.
A recent job run report plus an exception summary to help troubleshoot scheduling issues.
Run a Databricks SQL query to calculate sales and order counts by product line for the last 30 days, return the top 10 by sales descending, and include a short interpretation.
A result table from the query along with a brief business interpretation.
Explore Databricks metadata, run SQL, and analyze lineage for data discovery.
Search and explore Databricks AWS documentation with semantic search tools.
Run, test, and deploy code on Databricks clusters using natural language.
Build and deploy a production-ready MCP server for Databricks Apps.
Safely explore, profile, and query data with read-only SQL over MCP.
Turn existing APIs and databases into MCP tools for direct AI use.